Software Engineer III

High-visibility platform work sits at the center of this role within Enterprise Technology, AI and Machine Learning and Data Platforms at JPMorganChase. You will design, build, and operate platform capabilities that help teams develop, evaluate, and run agent-based solutions powered by LLMs. The scope includes end-to-end ownership, responsible and reliable delivery, and collaboration across engineering, data, security, and risk and compliance stakeholders. The location is New York, NY (onsite), with a salary range of USD 137,750 - 185,000 per yearly.

What you’ll do

• Deliver end-to-end platform features for agent-based artificial intelligence use cases, including technical design, production deployment, monitoring, and ongoing improvements
• Build and maintain reusable services and components that enable teams to create, evaluate, and operate LLM-powered agents at scale
• Implement evaluation and testing approaches for LLM systems, including quality measurement, regression testing, and error analysis to improve reliability over time
• Develop observability capabilities such as tracing, metrics, logs, and analytics to support healthy operations and fast troubleshooting
• Apply security, safety, and governance-by-design patterns, including guardrails, access controls, and audit-ready operational practices aligned to security and governance requirements
• Work with product managers and stakeholders to define success metrics, prioritize work, and deliver measurable business impact
• Partner across engineering, data, security, and risk and compliance stakeholders to ensure solutions are secure, stable, and scalable
• Create clear documentation and reference implementations that accelerate adoption and promote responsible, consistent engineering practices

Qualifications

• Formal training or certification on software engineering concepts plus 3+ years applied experience
• Proficiency in Python with strong software engineering fundamentals, including testing practices, version control, and code review
• Experience building and operating production services, including incident readiness, performance tuning, and operational stability for data-intensive systems
• Hands-on experience delivering machine learning and/or LLM-enabled features into production environments, including monitoring and post-deployment iteration
• Practical experience with prompt engineering and retrieval-augmented generation (RAG), including evaluation methods and quality measurement
• Ability to design maintainable systems and make sound technical decisions through ambiguity while balancing delivery speed, risk, and long-term sustainability
• Strong communication skills, including explaining technical trade-offs to both technical and non-technical stakeholders
• Strong collaboration skills and demonstrated ability to partner effectively across teams to deliver outcomes

Helpful technologies and experience

Experience with Python and LLM agent and platform tooling such as retrieval-augmented generation (RAG), prompt engineering, LangGraph, LlamaIndex, CI/CD, Docker, Kubernetes, vector databases, embedding pipelines, and Amazon Web Services and Databricks is relevant.

Benefits

• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching